You Cannot Manage Data from Your Cubicle!

GET OUT THERE!!!

You can’t do anything of true significance in the data space sitting in front of your computer. You have to get out there and engage with people, develop a deep understanding of the nature of the business, the ways it uses data to create value, the (seemingly endless) ways it fouls data up and misuses it, the fears and aspirations people have about data, and the politics that surround it.

I know some readers are reacting in horror, even anger, muttering things like “I’ve already got too much to do. I barely have time to do my job and keep up with the latest technologies” under their breath.

But I mean every word! I know a bit about data quality, analytics, metadata management, data strategy, and building strong organizations for data. So let’s take a look at a few.

First, data quality: The essence of data quality involves creating data correctly, the first time, so that it will meet customer needs. This means you have to know who the customers are, which data are most important, and what happens when the data are erred. It also means you have to know where the data were created, the details of how it was created, and the depth or awareness data creators have about customer needs. It means you have to connect data customers and data creators, help them find common ground, and lead improvement activities. You cannot do this work sitting in front of your computer. It is true that you will also have to create measurements and build in controls—activities you will do at your computer. But the most important work is with others.

Second, analytics: As I’ve pointed out elsewhere, “…. But great data scientists know they must do more. They recognize there are nuances and quality issues in the data they can’t understand sitting at their desks. They recognize that the world is filled with “soft data,” relevant sights, sounds, smells, tastes, and textures that are yet to be digitized—and hence are unavailable to those working at their computers. Things like the electricity in the air at a political rally, the smell on a cancer patient’s breath, and the fear in the eyes of an executive faced with an unexpected threat. They know they must understand the larger context, the real problems and opportunities, how decision makers decide, and how their predictions will be used.

“Great data scientists know the only way to acquire this smorgasbord of information is to go get it….”

Enough said. You can’t do this work sitting at your computer.

Third, metadata management: Let’s just consider data models. Good data models capture the essence of business language succinctly and accurately. Even better ones help simplify that language, improving day-in, day-out communications and not just computer-to-computer communications. And, as everyone knows, you can’t capture the subtleties and nuance in a language unless you speak it everyday!

I suppose it would be okay to sit at your computer terminal if the business spoke C++, SQL, Python, and XML. But they don’t. The business has its own language—actually I should say languages. Thus Finance has its own financial language, logistics its own language, and Human Resources its own. People who drill for oil have a language all their own. So do people who trade bonds, people who labor to cure cancer, and people who try to make peace in the world.

The only way to learn the language of business well enough to create great data models is to speak it. You can’t learn the language sitting in front of your computer. You have to get out there.

I hope readers trust that I could add similar paragraphs on data strategy and building strong organizations. I’m pretty sure most have gotten my main message already.

So why don’t more data people get out there? There are certainly lots of reasons. It is easy to see data as “the stuff contained in our computers;” and this perspective is partially true.

But a more complete and useful perspective recognizes that data is inextricably tied to the business. You can test this claim in your company—I’m pretty sure you’ll find it to be true. The implications are simple and profound. You can’t isolate yourself from some uncomfortable realities—ego, politics, culture, fear, organizational silos, ridiculous demands of Wall Street, and short-term thinking. Nor should you isolate yourself from the soaring human spirit—random acts of kindness, breathtaking new ideas, the extraordinary efforts some will take to satisfy a customer, and a fervent desire to improve.

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About Tom Redman

Tom Redman, the “Data Doc,” helps companies, including many of the Fortune 100, improve data quality. Those that follow his innovative approaches enjoy the many benefits of far-better data, including far lower cost. He is the author of Getting In Front on Data: The Who Does What (Technics Publications, 2016) and Data Driven (Harvard Business Review, 2008). His articles have appeared in many publications, including Harvard Business Review, The Wall Street Journal and MIT Sloan Management Review. Tom started his career at Bell Labs, where he led the Data Quality Lab. He has a Ph.D. is in Statistics and two patents.